70: Discrete Math and Probability. Programming Computers Superpower! - - PowerPoint PPT Presentation

70: Discrete Math and Probability.

Programming Computers ≡ Superpower! What are your super powerful programs doing? Logic and Proofs! Induction ≡ Recursion. What can computers do? Work with discrete objects. Discrete Math = ⇒ immense application. Computers learn and interact with the world? E.g. machine learning, data analysis. Probability! See note 1, for more discussion.

Admin.

Course Webpage: inst.cs.berkeley.edu/~cs70/sp16 Explains policies, has homework, midterm dates, etc. Two midterms, final. midterm 1 before drop date. (2/16) midterm 2 before grade option change. (3/29) Questions = ⇒ piazza: piazza.com/berkeley/spring2016/cs70 Also: Available after class. Assessment: Two options: Test Only. Midterm 1: 25% Midterm 2: 25% Final: 49% Sundry: 1% Test plus Homework. Test Only Score: 85% Homework Score: 15%

Instructor/Admin

Instructors: Satish Rao and Jean Walrand. Both are available throughout the course. Office hours or by email, technical and administrative. Satish Rao: mostly discrete math. Jean Walrand: mostly probability.

I ¡was ¡born ¡in ¡Belgium(1) ¡and ¡came ¡to ¡Berkeley ¡for ¡my ¡

• PhD. ¡ ¡I ¡have ¡been ¡teaching ¡at ¡UCB ¡since ¡1982. ¡ ¡

¡ My ¡wife ¡and ¡I ¡live ¡in ¡Berkeley. ¡ ¡We ¡have ¡two ¡ daughters ¡(UC ¡alumni ¡– ¡Go ¡Bears!). ¡We ¡like ¡to ¡ski ¡and ¡ play ¡tennis ¡(both ¡poorly). ¡ ¡We ¡enjoy ¡classical ¡music ¡ and ¡jazz. ¡ ¡ ¡ ¡ My ¡research ¡interests ¡include ¡stochasLc ¡systems, ¡ networks ¡and ¡game ¡theory. ¡ Jean ¡Walrand ¡– ¡Prof. ¡of ¡EECS ¡– ¡UCB ¡ 257 ¡Cory ¡Hall ¡– ¡walrand@berkeley.edu ¡ (1) ¡

Satish Rao

17th year at Berkeley. PhD: Long time ago, far far away. Research: Theory (Algorithms) Taught: 170, 174, 70, 270, 273, 294, 375, ... Recovering Helicopter(ish) parent of 3 College(ish) kids.

Wason’s experiment:1

Suppose we have four cards on a table:

◮ 1st about Alice, 2nd about Bob, 3rd Charlie, 4th Donna. ◮ Card contains person’s destination on one side,

and mode of travel.

◮ Consider the theory:

“If a person travels to Chicago, he/she flies.”

◮ Suppose you see that Alice went to Baltimore, Bob drove,

Charlie went to Chicago, and Donna flew.

Alice Baltimore Bob drove Charlie Chicago Donna flew

◮ Which cards do you need to flip to test the theory?

Answer: Later.

CS70: Lecture 1. Outline.

Today: Note 1. Note 0 is background. Do read/skim it. The language of proofs!

• 1. Propositions.
• 2. Propositional Forms.
• 3. Implication.
• 4. Truth Tables
• 5. Quantifiers
• 6. More De Morgan’s Laws

Propositions: Statements that are true or false.

√ 2 is irrational Proposition True 2+2 = 4 Proposition True 2+2 = 3 Proposition False 826th digit of pi is 4 Proposition False Johny Depp is a good actor Not a Proposition All evens > 2 are sums of 2 primes Proposition False 4+5 Not a Proposition. x +x Not a Proposition. Alice travelled to Chicago Proposition. False Again: “value” of a proposition is ... True or False

Propositional Forms.

Put propositions together to make another... Conjunction (“and”): P ∧Q “P ∧Q” is True when both P and Q are True . Else False . Disjunction (“or”): P ∨Q “P ∨Q” is True when at least one P or Q is True . Else False . Negation (“not”): ¬P “¬P” is True when P is False . Else False . Examples:

¬ “(2+2 = 4)”

– a proposition that is ... False “2+2 = 3” ∧ “2+2 = 4” – a proposition that is ... False “2+2 = 3” ∨ “2+2 = 4” – a proposition that is ... True

Propositional Forms: quick check!

P = “ √ 2 is rational” Q = “826th digit of pi is 2” P is ...False . Q is ...True . P ∧Q ... False P ∨Q ... True ¬P ... True

Put them together..

Propositions: P1 - Person 1 rides the bus. P2 - Person 2 rides the bus. .... But we can’t have either of the following happen; That either person 1

• r person 2 ride the bus and person 3 or 4 ride the bus. Or that

person 2 or person 3 ride the bus and that either person 4 ride the bus or person 5 doesn’t. Propositional Form: ¬(((P1 ∨P2)∧(P3 ∨P4))∨((P2 ∨P3)∧(P4 ∨¬P5))) Can person 3 ride the bus? Can person 3 and person 4 ride the bus together? This seems ...complicated. We can program!!!! We need a way to keep track!

Truth Tables for Propositional Forms.

P Q P ∧Q T T T T F F F T F F F F P Q P ∨Q T T T T F T F T T F F F Notice: ∧ and ∨ are commutative. One use for truth tables: Logical Equivalence of propositional forms! Example: ¬(P ∧Q) logically equivalent to ¬P ∨¬Q ...because the two propositional forms have the same... ....Truth Table! P Q ¬(P ∨Q) ¬P ∧¬Q T T F F T F F F F T F F F F T T DeMorgan’s Law’s for Negation: distribute and flip! ¬(P ∧Q) ≡ ¬P ∨¬Q ¬(P ∨Q) ≡ ¬P ∧¬Q

Distributive?

P ∧(Q ∨R) ≡ (P ∧Q)∨(P ∧R)? Simplify: (T ∧Q) ≡ Q, (F ∧Q) ≡ F. Cases: P is True . LHS: T ∧(Q ∨R) ≡ (Q ∨R). RHS: (T ∧Q)∨(T ∧R) ≡ (Q ∨R). P is False . LHS: F ∧(Q ∨R) ≡ F. RHS: (F ∧Q)∨(F ∧R) ≡ (F ∨F) ≡ F. P ∨(Q ∧R) ≡ (P ∨Q)∧(P ∨R)? Simplify: T ∨Q ≡ T, F ∨Q ≡ Q. Foil 1: (A∨B)∧(C ∨D) ≡ (A∧C)∨(A∧D)∨(B ∧C)∨(B ∧D)? Foil 2: (A∧B)∨(C ∧D) ≡ (A∨C)∧(A∨D)∧(B ∨C)∧(B ∨D)?

Implication.

P = ⇒ Q interpreted as If P, then Q. True Statements: P, P = ⇒ Q. Conclude: Q is true. Examples: Statement: If you stand in the rain, then you’ll get wet. P = “you stand in the rain” Q = “you will get wet” Statement: “Stand in the rain” Can conclude: “you’ll get wet.” Statement: If a right triangle has sidelengths a ≤ b ≤ c, then a2 +b2 = c2. P = “a right triangle has sidelengths a ≤ b ≤ c”, Q = “a2 +b2 = c2”.

Non-Consequences/consequences of Implication

The statement “P = ⇒ Q”

• nly is False if P is True and Q is False .

False implies nothing P False means Q can be True or False Anything implies true. P can be True or False when Q is True If chemical plant pollutes river, fish die. If fish die, did chemical plant pollute river? Not necessarily. P = ⇒ Q and Q are True does not mean P is True Be careful! Instead we have: P = ⇒ Q and P are True does mean Q is True . The chemical plant pollutes river. Can we conclude fish die? Some Fun: use propositional formulas to describe implication? ((P = ⇒ Q)∧P) = ⇒ Q.

Implication and English.

P = ⇒ Q

◮ If P, then Q. ◮ Q if P.

Just reversing the order.

◮ P only if Q.

Remember if P is true then Q must be true. this suggests that P can only be true if Q is true. since if Q is false P must have been false.

◮ P is sufficient for Q.

This means that proving P allows you to conclude that Q is true.

◮ Q is necessary for P.

For P to be true it is necessary that Q is true. Or if Q is false then we know that P is false.

Truth Table: implication.

P Q P = ⇒ Q T T T T F F F T T F F T P Q ¬P ∨Q T T T T F F F T T F F T ¬P ∨Q ≡ P = ⇒ Q. These two propositional forms are logically equivalent!

Contrapositive, Converse

◮ Contrapositive of P =

⇒ Q is ¬Q = ⇒ ¬P.

◮ If the plant pollutes, fish die. ◮ If the fish don’t die, the plant does not pollute.

(contrapositive)

◮ If you stand in the rain, you get wet. ◮ If you did not stand in the rain, you did not get wet.

(not contrapositive!) converse!

◮ If you did not get wet, you did not stand in the rain.

(contrapositive.) Logically equivalent! Notation: ≡. P = ⇒ Q ≡ ¬P ∨Q ≡ ¬(¬Q)∨¬P ≡ ¬Q = ⇒ ¬P.

◮ Converse of P =

⇒ Q is Q = ⇒ P. If fish die the plant pollutes. Not logically equivalent!

◮ Definition: If P =

⇒ Q and Q = ⇒ P is P if and only if Q or P ⇐ ⇒ Q. (Logically Equivalent: ⇐ ⇒ . )

Variables.

Propositions?

◮ ∑n

i=1 i = n(n+1) 2

.

◮ x > 2 ◮ n is even and the sum of two primes

• No. They have a free variable.

We call them predicates, e.g., Q(x) = “x is even” Same as boolean valued functions from 61A or 61AS!

◮ P(n) = “∑n

i=1 i = n(n+1) 2

.”

◮ R(x) = “x > 2” ◮ G(n) = “n is even and the sum of two primes” ◮ Remember Wason’s experiment!

F(x) = “Person x flew.” C(x) = “Person x went to Chicago

◮ C(x) =

⇒ F(x). Theory from Wason’s. If person x goes to Chicago then person x flew. Next: Statements about boolean valued functions!!

Quantifiers..

There exists quantifier: (∃x ∈ S)(P(x)) means ”There exists an x in S where P(x) is true.” For example: (∃x ∈ N)(x = x2) Equivalent to “(0 = 0)∨(1 = 1)∨(2 = 4)∨...” Much shorter to use a quantifier! For all quantifier; (∀x ∈ S) (P(x)). means “For all x in S, we have P(x) is True .” Examples: “Adding 1 makes a bigger number.” (∀x ∈ N) (x +1 > x) ”the square of a number is always non-negative” (∀x ∈ N)(x2 >= 0) Wait! What is N?

Quantifiers: universes.

Proposition: “For all natural numbers n, ∑n

i=1 i = n(n+1) 2

.” Proposition has universe: “the natural numbers”. Universe examples include..

◮ N = {0,1,...} (natural numbers). ◮ Z = {...,−1,0,...} (integers) ◮ Z+ (positive integers) ◮ R (real numbers) ◮ Any set: S = {Alice,Bob,Charlie,Donna}. ◮ See note 0 for more!

Back to: Wason’s experiment:1

Theory: “If a person travels to Chicago, he/she flies.” Suppose you see that Alice went to Baltimore, Bob drove, Charlie went to Chicago, and Donna flew. Which cards do you need to flip to test the theory? P(x) = “Person x went to Chicago.” Q(x) = “Person x flew” Statement/theory: ∀x ∈ {A,B,C,D},P(x) = ⇒ Q(x) P(A) = False . Do we care about Q(A)?

• No. P(A) =

⇒ Q(A), when P(A) is False , Q(A) can be anything. Q(B) = False . Do we care about P(B)?

• Yes. P(B) =

⇒ Q(B) ≡ ¬Q(B) = ⇒ ¬P(B). So P(Bob) must be False . P(C) = True . Do we care about P(C)?

• Yes. P(C) =

⇒ Q(C) means Q(C) must be true. Q(D) = True . Do we care about P(D)?

• No. P(D) =

⇒ Q(D) holds whatever P(D) is when Q(D) is true. Only have to turn over cards for Bob and Charlie.

More for all quantifiers examples.

◮ “doubling a number always makes it larger”

(∀x ∈ N) (2x > x) False Consider x = 0 Can fix statement... (∀x ∈ N) (2x ≥x) True

◮ “Square of any natural number greater than 5 is greater than 25.”

(∀x ∈ N)(x > 5 = ⇒ x2 > 25). Idea alert: Restrict domain using implication. Note that we may omit universe if clear from context.

Quantifiers..not commutative.

◮ In English: “there is a natural number that is the square of every

natural number”. (∃y ∈ N) (∀x ∈ N) (y = x2) False

◮ In English: “the square of every natural number is a natural

number.” (∀x ∈ N)(∃y ∈ N) (y = x2) True

Quantifiers....negation...DeMorgan again.

Consider ¬(∀x ∈ S)(P(x)), English: there is an x in S where P(x) does not hold. That is, ¬(∀x ∈ S)(P(x)) ⇐ ⇒ ∃(x ∈ S)(¬P(x)). What we do in this course! We consider claims. Claim: (∀x) P(x) “For all inputs x the program works.” For False , find x, where ¬P(x). Counterexample. Bad input. Case that illustrates bug. For True : prove claim. Next lectures...

Negation of exists.

Consider ¬(∃x ∈ S)(P(x)) English: means that for all x in S , P(x) does not hold. That is, ¬(∃x ∈ S)(P(x)) ⇐ ⇒ ∀(x ∈ S)¬P(x).

Which Theorem?

Theorem: (∀n ∈ N) ¬(∃a,b,c ∈ N) (n ≥ 3 = ⇒ an +bn = cn) Which Theorem? Fermat’s Last Theorem! Remember Special Triangles: for n = 2, we have 3,4,5 and 5,7, 12 and ... 1637: Proof doesn’t fit in the margins. 1993: Wiles ...(based in part on Ribet’s Theorem) DeMorgan Restatement: Theorem: ¬(∃n ∈ N) (∃a,b,c ∈ N) (n ≥ 3 = ⇒ an +bn = cn)

Summary.

Propositions are statements that are true or false. Proprositional forms use ∧,∨,¬. Propositional forms correspond to truth tables. Logical equivalence of forms means same truth tables. Implication: P = ⇒ Q ⇐ ⇒ ¬P ∨Q. Contrapositive: ¬Q = ⇒ ¬P Converse: Q = ⇒ P Predicates: Statements with “free” variables. Quantifiers: ∀x P(x), ∃y Q(y) Now can state theorems! And disprove false ones! DeMorgans Laws: “Flip and Distribute negation” ¬(P ∨Q) ⇐ ⇒ (¬P ∧¬Q) ¬∀x P(x) ⇐ ⇒ ∃x ¬P(x). Next Time: proofs!